CN108898559A - Atmospheric dispersion correction method based on image deconvolution - Google Patents
Atmospheric dispersion correction method based on image deconvolution Download PDFInfo
- Publication number
- CN108898559A CN108898559A CN201810634255.1A CN201810634255A CN108898559A CN 108898559 A CN108898559 A CN 108898559A CN 201810634255 A CN201810634255 A CN 201810634255A CN 108898559 A CN108898559 A CN 108898559A
- Authority
- CN
- China
- Prior art keywords
- image
- deconvolution
- atmospheric dispersion
- column
- atmospheric
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
- 239000006185 dispersion Substances 0.000 title claims abstract description 70
- 238000000034 method Methods 0.000 title claims abstract description 16
- 238000012937 correction Methods 0.000 title claims abstract description 10
- 238000004422 calculation algorithm Methods 0.000 claims abstract description 18
- 230000003287 optical effect Effects 0.000 claims abstract description 18
- 238000013461 design Methods 0.000 claims abstract description 9
- 230000000694 effects Effects 0.000 claims abstract description 7
- 238000002715 modification method Methods 0.000 claims description 10
- 238000003384 imaging method Methods 0.000 claims description 5
- 238000004364 calculation method Methods 0.000 claims description 2
- 230000002441 reversible effect Effects 0.000 claims description 2
- 230000008569 process Effects 0.000 abstract description 3
- 238000011084 recovery Methods 0.000 abstract description 2
- 239000013307 optical fiber Substances 0.000 abstract 1
- 230000009466 transformation Effects 0.000 description 8
- 238000012545 processing Methods 0.000 description 5
- 238000001514 detection method Methods 0.000 description 4
- 230000008901 benefit Effects 0.000 description 3
- 238000010586 diagram Methods 0.000 description 3
- 238000005516 engineering process Methods 0.000 description 3
- 238000003702 image correction Methods 0.000 description 3
- 238000004458 analytical method Methods 0.000 description 2
- 239000000463 material Substances 0.000 description 2
- 230000000007 visual effect Effects 0.000 description 2
- 238000010521 absorption reaction Methods 0.000 description 1
- 238000013459 approach Methods 0.000 description 1
- 238000005452 bending Methods 0.000 description 1
- 230000008859 change Effects 0.000 description 1
- 238000011157 data evaluation Methods 0.000 description 1
- 230000007423 decrease Effects 0.000 description 1
- 238000009792 diffusion process Methods 0.000 description 1
- 239000011159 matrix material Substances 0.000 description 1
- 230000007246 mechanism Effects 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 230000002969 morbid Effects 0.000 description 1
- 239000011435 rock Substances 0.000 description 1
- 238000004088 simulation Methods 0.000 description 1
- 238000001228 spectrum Methods 0.000 description 1
- 238000012360 testing method Methods 0.000 description 1
- 238000000844 transformation Methods 0.000 description 1
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T5/00—Image enhancement or restoration
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/30—Subject of image; Context of image processing
- G06T2207/30181—Earth observation
- G06T2207/30192—Weather; Meteorology
Landscapes
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Engineering & Computer Science (AREA)
- Theoretical Computer Science (AREA)
- Image Processing (AREA)
Abstract
The invention discloses an atmospheric dispersion correction method based on image deconvolution, which comprises the following specific processes: step S1: aiming at an image to be corrected of the telescope, estimating an image dispersion index caused by atmospheric dispersion by using an Elden model; step S2: performing edge continuation on each line of data in the image to maximally approximate the image convolution effect; step S3: and correcting the atmospheric dispersion influence by adopting an image deconvolution algorithm on each column of data after the extension. The invention simulates the data after direct convolution of the image to the maximum extent based on the reversibility of convolution and deconvolution under certain conditions, and then performs deconvolution recovery. The method corrects the image blur caused by atmospheric dispersion on the basis of image deconvolution, and reduces the design complexity of an optical system compared with the traditional prism correction and optical fiber correction.
Description
Technical field
The invention belongs to ground astronomy and Space-objects Observation fields, and in particular to the atmospheric dispersion based on image deconvolution
Modification method carries out atmospheric dispersion correction using ground photo-electric telescope of the image deconvolution algorithm to the big visual field of heavy caliber, makes
Telescope obtains the image being more clear.
Background technique
With the increase of ground photo-electric telescope bore and focal length, the image quality of telescope is influenced to be cured by atmospheric dispersion
Hair is serious.In short focus optical system, the picture of fixed star is rendered as dot, and the picture point of long focus optical system becomes short-term, leads to figure
Image sharpness decline, influences the detection and resolution to dark weak signal target (referring to document [1] bright name, Lv Tianyu, Wu little Xia, Hao Liang, Zhao
Golden space " influence and correction of the atmospheric dispersion to 4m telescope Imaging Resolution ", Chinese Optical, 2015,8 (5):814-822.).
The producing cause of atmospheric dispersion is：After atmosphere is passed through from the light of celestial body, influenced to produce light by atmosphere
Raw refraction.For the light of different wave length, air index is different, and the bending generated after atmosphere is also different, thus
Formed atmospheric dispersion (referring to document [2] Liu Genrong, Yuan Xiang rock the atmospheric dispersion of LAMOST telescope " correct ", Astronomica Sinica,
2005,46(3):331-342. and document [3] Zhang Xuejun, the Jiang Wen Chinese " atmospheric refraction and the calculating of the numerical value of atmospheric dispersion and result
Analysis ", photoelectric project, 2002,29 (2):1-5.).Due to the influence of atmospheric refraction, in non-zenith region, the target observed
Pitch angle and the actual pitch angle of target have certain difference.On the other hand, non-zenith target (even point source) can be in pitching side
To broadening is generated, so that the star image in image planes becomes a discrete spectrum by a dot.
Traditional atmospheric dispersion bearing calibration is in Optical System Design dispersion corrector.When aperture of mirror of looking in the distance is larger, and
In the case where taking into account big view field imaging requirement, the design of dispersion corrector needs to take into account heavy caliber and big visual field, and optical system is wanted
Guarantee the image quality of full filed, while having the correction taken into account to atmospheric dispersion again, increases the design difficulty of optical system；Greatly
Complexion dissipates the optical material that corrector generally requires high dispersion, and the short-wave absorption of these materials is big, influences transmissivity of optical system；
Atmospheric dispersion is with the difference at the observation elevation angle, and atmospheric dispersion can also change therewith, therefore atmospheric dispersion corrector is needed with telescope
The elevation angle is adjusted.In the adjustment of dispersion corrector, it is ensured that the eccentric of optical system requires, and cannot influence optical system imaging
Quality, therefore it is required that adjustment mechanism has very high precision.Cause system complex, technology difficult for atmospheric dispersion optical correction method
The characteristics of degree increases promotes us using image procossing by the way of to solve the problems, such as atmospheric dispersion, reduce optics of telescope design,
The difficulty of processing, detection, adjustment and adjustment.
Telescope is imaged in terms of mathematical angle, i.e., regards atmospheric dispersion model as a convolution kernel, original image is through pulleying
After product nuclear convolution, the shooting image after obtaining dispersive influence.Theoretically, the image and convolution kernel after known dispersion influence
In the case of, it is calculated by deconvolution, so that it may recover original image.
Most difficult problem is when solving restoration equation through being commonly encountered ill-conditioning problem and singular problem in image restoration.Ignore
The influence of noise and non-linear factor a, it is known that column in image can be expressed as by atmospheric dispersion influence：
fi(y) * h (w)=gi(y) (1)
Transformation or operator T can be defined, T is carried out to f and converts to obtain g, i.e.,：
T{fi}→gi (2)
The problem of image restoration is exactly to find an inverse transformation T-1, so that：
T-1{gi}→fi (3)
It is said from mathematical meaning, the problem of image restoration is the existence and unicity problem that inverse transformation is discussed.If inverse
Transformation is not present, then in theory from pure mathematics, f cannot be restored from g to be come out.Meanwhile the disturbance of g very little may make
At the very big disturbance of f.It is expressed mathematically as：
T-1{gi+ε}→fi+δ (4)
In formula, ε is arbitrarily small disturbed value；δ is the corresponding disturbance for causing f.
When δ > > ε, i.e. δ are no longer insignificant any a small amount of.Cause to will appear three kinds of feelings during inversion solves
Condition：First is that the problem of inverse transformation is not present, referred to as singular problem；Secondly, inverse transformation T-1There may be but it is not single, it is understood that there may be
Multiple inverse transformations；Finally, even if inverse transformation exist and it is single, but it may morbid state.
How to solve the ill-conditioning problem in inversion solution procedure is the key that algorithm, at present it is not yet found that solving the problems, such as this
Technology.
Summary of the invention
The present invention provides a kind of image deconvolution algorithm for correcting atmospheric dispersion shadow to overcome the shortcomings of existing scheme
It rings.The method overcome difficulty of traditional optics revised law in design, processing, detection, adjustment and adjustment, take full advantage of
The system parameter and survey station information of telescope ensure that the image quality of telescope while correcting atmospheric dispersion.
The technical solution adopted by the present invention is：Atmospheric dispersion modification method based on image deconvolution, using image algorithm
Amendment substitutes traditional optical correction method, greatly reduces the complexity of Optical System Design, implementation step includes：
Step S1：For the image to be corrected of telescope, image caused by atmospheric dispersion is estimated more using Elden model
Dissipate index；
Step S2：Edge extension is carried out to column data each in image, farthest close to image convolution effect；
Step S3：To each column data after continuation, influenced using the amendment atmospheric dispersion of image deconvolution algorithm.
The principle of the present invention is：Convolution is reversible under certain condition.
The advantages of present invention is compared with existing optics revised law is：
(1) image correction algorithm reduces optics of telescope design, the difficulty of processing, detection, adjustment and adjustment, so that greatly
It is easier that complexion dissipates realization of the amendment on heavy caliber Large Area Telescope.
(2) the processing approach of image correction algorithm is handled the image of telescope shooting, not to optical system
Carry out any modification.Thus, while correcting atmospheric dispersion influences, the image quality of telescope will not be impacted.
(3) when image correction method restores target in image, it is higher that target restores degree, and arithmetic speed is fast, can
To substantially meet engineering demand.
Detailed description of the invention
Fig. 1 is image processing flow figure of the invention；
Fig. 2 is the original image schematic diagram not influenced by atmospheric dispersion of the invention；
Fig. 3 is the image schematic diagram that simulation of the invention is influenced by atmospheric dispersion；
Fig. 4 a be image of the invention in one be listed in by dispersive influence after grey scale curve；
Fig. 4 b is the grey scale curve in image of the invention after a column border continuation；
Fig. 4 c is the grey scale curve in image of the invention after a column deconvolution；
Fig. 5 is that this algorithm of the invention corrects the schematic diagram after atmospheric dispersion influence；
Fig. 6 a is original asterism grayscale image of the invention；
Fig. 6 b is the three-dimensional figure of original asterism of the invention；
Fig. 7 a be it is of the invention influenced by atmospheric dispersion after asterism grayscale image；
Fig. 7 b be it is of the invention influenced by atmospheric dispersion after asterism three-dimensional figure；
Fig. 8 a is the asterism grayscale image after the amendment atmospheric dispersion influence of the invention using this algorithm；
Fig. 8 b is the asterism three-dimensional figure after the amendment atmospheric dispersion influence of the invention using this algorithm.
Specific embodiment
To make the objectives, technical solutions, and advantages of the present invention clearer, below in conjunction with specific embodiment, and reference
Attached drawing, the present invention is described in more detail.
When the present invention is suitable for ground telescope to astronomical and extraterrestrial target progress track up, shooting asterism is solved by big
Fuzzy problem caused by gas dispersive influence.Specifically, the atmospheric dispersion modification method step based on image deconvolution includes：
Step S1：For the image to be corrected of telescope, image caused by atmospheric dispersion is estimated more using Elden model
Dissipate index；
Step S2：Edge extension is carried out to column data each in image, farthest close to image convolution effect；
Step S3：To each column data after continuation, influenced using the amendment atmospheric dispersion of image deconvolution algorithm.
The process of image deconvolution algorithm is as shown in Figure 1, shooting figure to be influenced by atmospheric dispersion in the method for the present invention
As on the basis of, according to telescope parameter and survey station environment, target disperse index is estimated.Several columns are divided the image into again, it will be every
One column gray value of image inputs continuation model and carries out edge extension, and deconvolution.Finally, by the image column of deconvolution is completed again
It is combined into new images, the image after as restoring.It is because of big complexion in the present solution, image column is carried out continuation and deconvolution
It dissipates and only results in image in the vertical direction in the presence of diffusion.But when telescope shoot there are when image rotation, need first to image
Matrix operation is carried out, image rotation is eliminated, reuses this algorithm process.
Specifically, image deconvolution algorithm of the invention includes the following steps：
1. going out atmospheric dispersion value according to Elden model and telescope survey station data-evaluation first
Wherein, z indicates zenith distance, unit：Degree；Indicate atmospheric dispersion value, unit：Rad；WithTable respectively
Show corresponding wave band λ1To λ2Air index.The calculation formula of air index is：
Wherein, λ indicates imaging wavelength (μm), and T indicates temperature (DEG C), and P indicates atmospheric pressure (Pa).
2. according to the parameter of ground telescope, the image for calculating telescope shooting is influenced by atmospheric dispersion, it is caused more
Dissipate pixel number m.
Wherein, f indicates that the focal length (mm) of telescope, x indicate telescope pixel dimension (μm).
3. the image influenced by atmospheric dispersion successively to be extracted to the pixel value of each column.Image column pixel value is divided
Analysis replaces it with background gray scale if the head and the tail of image column have bright pixel point.
4. column each in the image (as shown in Figure 3) of telescope shooting influenced by atmospheric dispersion are inputted edge extension mould
Type simulates true convolution effect.
Wherein, after x indicates that the cell coordinate of the image column of input, m indicate that disperse pixel index, y indicate edge extension
Column cell coordinate, ginAnd goutImage column gray value after respectively representing input picture column sum of the grayscale values edge extension, meanwhile, it is right
In decimal p,【p】Indicate the integer part of decimal p.
5. being according to deconvolution operation, convolution kernel is carried out by the picturewide after continuation：
The length of convolution kernel：N=m+1, m are the pixel index of disperse.In image it is a certain be listed in influenced by atmospheric dispersion after
Fuzzy graph in and edge extension after, the gray value after deconvolution it is as shown in Figure 4.
6. the image column after deconvolution is spliced into complete image.
Fig. 3 shows the blurred picture that telescope is shot after atmospheric dispersion influences.Due to currently look in the distance mirror device with
And atmospheric dispersion amendment is carried out using the method for adding prism in the optical path, after true atmospheric dispersion influence can not be taken
Image.So the fuzzy graph in text is that true shooting image (Fig. 2) passes through the emulating image that image procossing obtains.
In order to test this algorithm to the recovery effect of asterism, an asterism in image is extracted, draws out it respectively
Restore the office in image (Fig. 8) in really shooting image (Fig. 6), the blurred picture (Fig. 7) influenced by atmospheric dispersion and deconvolution
Portion's figure and three-dimensional figure, and calculate signal-to-noise ratio and size of the asterism in three width images, such as following table：
1. target of table corresponds to characteristic after original image, atmospheric dispersion and after deconvolution
| Original image | After dispersion | After deconvolution | |
| Target sizes | 4×4 | 4×11 | 4×4 |
| Target peak signal-to-noise ratio | 494.76 | 92.35 | 494.25 |
| Target mean signal-to-noise ratio | 62.47 | 22.82 | 62.01 |
As can be seen from the above results, the method for the present invention amendment atmospheric dispersion influence can preferably recover original star
Point, the signal-to-noise ratio and size of target restore preferable.The above, the only specific embodiment in the present invention, but it is of the invention
Protection scope is not limited thereto, and any people for being familiar with the technology is within the technical scope disclosed by the invention, it will be appreciated that expects
Transform or replace, should all cover within the scope of the present invention.
Claims (6)
1. a kind of atmospheric dispersion modification method based on image deconvolution, which is characterized in that realize that step includes：
Step S1：For the image to be corrected of telescope, disperse index caused by atmospheric dispersion is estimated using Elden model；
Step S2：Edge extension is carried out to column data each in image, farthest close to image convolution effect；
Step S3：To each column data after continuation, influenced using the amendment atmospheric dispersion of image deconvolution algorithm.
2. the atmospheric dispersion modification method based on image deconvolution according to claim 1, which is characterized in that image algorithm is repaired
Traditional optical correction method is just being substituted, the complexity of Optical System Design can be substantially reduced.
3. the atmospheric dispersion modification method based on image deconvolution according to claim 1, which is characterized in that calculate big complexion
The step of image disperse index caused by dissipating, is as follows：
Step 31：Atmospheric dispersion value is estimated by Elden model
Wherein, z indicates zenith distance, unit：Degree；Indicate atmospheric dispersion value, unit：Rad；WithIt respectively indicates pair
Answer wave band λ1To λ2Air index, the calculation formula of air index is:
Wherein, λ indicates imaging wavelength (μm), and T indicates temperature (DEG C), and P indicates atmospheric pressure (Pa)；
Step 32：The asterism of ground telescope shooting, is influenced, the disperse pixel exponent m of generation by atmospheric dispersion,
Wherein, f indicates that the focal length (mm) of telescope, x indicate telescope pixel dimension (μm).
4. the atmospheric dispersion modification method based on image deconvolution according to claim 1, which is characterized in that prolong image border
The step of opening up model foundation is as follows：
Step 41：Successively extract each column in image；
Step 42：Image column pixel value is analyzed, if the head and the tail of image column have bright pixel point, the i.e. pixel of bright pixel point
Value>When background gray average+3* background variance, it is replaced with background gray scale；
Step 43：Edge extension is carried out by following edge extension model to each column data：
Wherein, x indicates that the cell coordinate of the image column of input, m indicate that disperse pixel index, y indicate the column picture after edge extension
First coordinate, ginAnd goutImage column gray value after respectively representing input picture column sum of the grayscale values edge extension, meanwhile, for small
Number p,【p】Indicate the integer part of decimal p.
5. the atmospheric dispersion modification method based on image deconvolution according to claim 1, which is characterized in that image deconvolution
Steps are as follows：
Step 51：Image column gray value after continuation is subjected to deconvolution, convolution kernel is：
The length of convolution kernel：N=m+1, m are the pixel index of disperse.
Step 52：Each column gradation data after deconvolution is reassembled into a width complete image.
6. the atmospheric dispersion modification method based on image deconvolution according to claim 1, which is characterized in that warp in image
Edge extension before product largely simulates the effect after the true convolution of image, so that deconvolution becomes reversible and single
One.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201810634255.1A CN108898559B (en) | 2018-06-20 | 2018-06-20 | Atmospheric dispersion correction method based on image deconvolution |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201810634255.1A CN108898559B (en) | 2018-06-20 | 2018-06-20 | Atmospheric dispersion correction method based on image deconvolution |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN108898559A true CN108898559A (en) | 2018-11-27 |
| CN108898559B CN108898559B (en) | 2021-11-19 |
Family
ID=64345546
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201810634255.1A Active CN108898559B (en) | 2018-06-20 | 2018-06-20 | Atmospheric dispersion correction method based on image deconvolution |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN108898559B (en) |
Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| EP1995588A1 (en) * | 2006-03-15 | 2008-11-26 | Ngk Insulators, Ltd. | Output correcting method of nox sensor |
| CN102436643A (en) * | 2011-11-02 | 2012-05-02 | 浙江大学 | Image defogging method facing to atmospheric scattering proximity effect |
| CN102445279A (en) * | 2010-10-14 | 2012-05-09 | 上海微电子装备有限公司 | Device and method for measuring wave lengths of interferometer |
| CN102930514A (en) * | 2012-09-27 | 2013-02-13 | 西安电子科技大学 | Rapid image defogging method based on atmospheric physical scattering model |
| CN104166960A (en) * | 2014-07-24 | 2014-11-26 | 中国科学院光电技术研究所 | Self-adaptive non-uniform fixed noise removing method based on scene |
| CN107832684A (en) * | 2017-10-26 | 2018-03-23 | 通华科技（大连）有限公司 | A kind of intelligent vein authentication method and system with independent learning ability |
| CN107966447A (en) * | 2017-11-14 | 2018-04-27 | 浙江大学 | A kind of Surface Flaw Detection method based on convolutional neural networks |
-
2018
- 2018-06-20 CN CN201810634255.1A patent/CN108898559B/en active Active
Patent Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| EP1995588A1 (en) * | 2006-03-15 | 2008-11-26 | Ngk Insulators, Ltd. | Output correcting method of nox sensor |
| CN102445279A (en) * | 2010-10-14 | 2012-05-09 | 上海微电子装备有限公司 | Device and method for measuring wave lengths of interferometer |
| CN102436643A (en) * | 2011-11-02 | 2012-05-02 | 浙江大学 | Image defogging method facing to atmospheric scattering proximity effect |
| CN102930514A (en) * | 2012-09-27 | 2013-02-13 | 西安电子科技大学 | Rapid image defogging method based on atmospheric physical scattering model |
| CN104166960A (en) * | 2014-07-24 | 2014-11-26 | 中国科学院光电技术研究所 | Self-adaptive non-uniform fixed noise removing method based on scene |
| CN107832684A (en) * | 2017-10-26 | 2018-03-23 | 通华科技（大连）有限公司 | A kind of intelligent vein authentication method and system with independent learning ability |
| CN107966447A (en) * | 2017-11-14 | 2018-04-27 | 浙江大学 | A kind of Surface Flaw Detection method based on convolutional neural networks |
Non-Patent Citations (6)
| Title |
|---|
| LAURENT M. MUGNIER 等: "Myopic deconvolution from wave-front sensing", 《JOURNAL OF THE OPTICAL SOCIETY OF AMERICA A-OPTICS IMAGE SCIENCE AND VISION》 * |
| WILL SAUNDERS 等: "Prime focus wide-field corrector designs with lossless atmospheric dispersion correction", 《CONFERENCE ON ADVANCES IN OPTICAL AND MECHANICAL TECHNOLOGIES FOR TELESCOPES AND INSTRUMENTATION》 * |
| 吕炜煜 等: "干旱地区大气折射对光电工程的影响", 《红外与激光工程》 * |
| 明名 等: "大气色散对4m望远镜成像分辨力的影响与校正", 《中国光学》 * |
| 朱莉: "短毫米波近程主被动阵列探测及成像技术研究", 《中国博士学位论文全文数据库 信息科技辑》 * |
| 马子扬 等: "图像反卷积边界效应的快速抑制算法", 《计算机辅助设计与图形学学报》 * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN108898559B (en) | 2021-11-19 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN104537620B (en) | Direction-adaptive image deblurring method | |
| Kronander et al. | A unified framework for multi-sensor HDR video reconstruction | |
| CN104091312B (en) | A kind of simple lens formation method according to image spectrum information extraction fuzzy core priori | |
| CN104834089B (en) | Wavefront coding imaging system and super-resolution processing method | |
| US20140105515A1 (en) | Stabilizing and Deblurring Atmospheric Turbulence | |
| CN204719330U (en) | Wavefront coded imaging system | |
| CN106023108A (en) | Image defogging algorithm based on boundary constraint and context regularization | |
| Hui et al. | Image restoration of optical sparse aperture systems based on a dual target network | |
| US10521918B2 (en) | Method and device for filtering texture, using patch shift | |
| CN115018725A (en) | Diffraction image restoration method based on block minimum pixel prior | |
| Lin et al. | Non-blind optical degradation correction via frequency self-adaptive and finetune tactics | |
| Jiang et al. | Local adaptive prior-based image restoration method for space diffraction imaging systems | |
| US20200074604A1 (en) | Image compositing system, image compositing method, and image compositing program recording medium | |
| CN108898559A (en) | Atmospheric dispersion correction method based on image deconvolution | |
| Zhou et al. | Single image dehazing algorithm based on modified dark channel prior | |
| Tezaur et al. | A system for estimating optics blur psfs from test chart images | |
| Schmidt et al. | Real-time image restoration for space-object imaging | |
| CN204613515U (en) | Wavefront coding imaging system | |
| Belov et al. | Spatial interpolation methods for spectral-spatial remote sensing image super-resolution algorithm based on gradient descent approach | |
| Qu et al. | Joint regularization and low-rank fusion for atmospheric turbulence removal | |
| Kong et al. | The Experimental Demonstration of Correcting the Atmospheric Dispersion Using Image Processing Based on Edge Extension | |
| Wen et al. | Fast Restoration of Aberration-Degraded Extended Object Based on Local Region Abstraction | |
| Lin et al. | A Framework for Generating High-Resolution Seamless Remote Sensing Images for Regional-Scale Areas | |
| La Camera et al. | AIRY: a complete tool for the simulation and the reconstruction of astronomical images | |
| Zhang et al. | Cascaded Temporal and Spatial Attention Network for solar adaptive optics image restoration |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |